View source on GitHub |
Greedily selects a subset of bounding boxes in descending order of score.
tf.image.non_max_suppression_overlaps(
overlaps,
scores,
max_output_size,
overlap_threshold=0.5,
score_threshold=float('-inf'),
name=None
)
Prunes away boxes that have high overlap with previously selected boxes.
N-by-n overlap values are supplied as square matrix.
The output of this operation is a set of integers indexing into the input
collection of bounding boxes representing the selected boxes. The bounding
box coordinates corresponding to the selected indices can then be obtained
using the tf.gather
operation. For example:
selected_indices = tf.image.non_max_suppression_overlaps(
overlaps, scores, max_output_size, iou_threshold)
selected_boxes = tf.gather(boxes, selected_indices)
Returns | |
---|---|
selected_indices
|
A 1-D integer Tensor of shape [M] representing the
selected indices from the overlaps tensor, where M <= max_output_size .
|